Table of Contents
Some other AI Drug Development Companies
| S. no. | Company name | Website | Small description |
| 1 | Atomwise | atomwise.com | Transforming virtual screening through deep learning |
| 2 | Molecule AI | moleculeai.com | AI-driven platform for correct drug design. |
| 3 | TwoXAR | twoxar.com | Rapid assessment and listing of drug candidates. |
| 4 | Recce Pharmaceuticals | recce.com | Incorporation of AI in emerging innovative antibiotics. |
| 5 | Biosymetrics | biosymetrics.com | United data analytics platform for all-inclusive insights. |
| 6 | Cyclica | cyclicarx.com | Survey of polypharmacology and network pharmacology. |
| 7 | Ardigen | ardigen.com | AI progressions in immunotherapy research. |
| 8 | Healx | healx.io | AI-driven rare disease drug discovery lecturing unmet needs. |
Conclusion
The development of AI tools consistently keeps an aim for decreasing difficulties that drug Development companies face. The existing healthcare sector is facing numerous complicated challenges like enhanced cost of drugs and other therapies, and society requires specified substantial changes in this area.
With AI, it’s possible to manufacture drugs, customize medicines with desired dosage, release parameters and other such needed aspects.
AI-based technologies not only help in speeding up the time required for product quality and overall safety of the manufacturing process and offer good utilization of available resources in addition to cost-efficient therapies by enhancing the vitality of automation.
Also read:
- Top AI Biotech Companies | Labmonk
- Top CAR-T Cell Therapy Companies You Should Know | Labmonk
- How to Become a Life Science Consultant (with Salary and Skills) | Labmonk
- How to Become a Medical Scribe | Labmonk
- Best Biotech Companies to Work for | Labmonk
- Wet Lab vs Dry Lab | Labmonk
- The Top 25 Pharmaceutical Companies in New Jersey | Labmonk
- What is a CRA Clinical Research Associate | Labmonk
- Top 25 Online Biomedical Science Degree | Labmonk
FAQs
Does AI have a role in drug development?
Yes, AI can support several stages of drug discovery in many ways which involve disease recognition, acquisition of target, computational screening, prediction of drug toxicity, gene editing etc.
What changes AI can bring in drug development?
It helps in speeding up the testing process and reduces the elongated period in which the biological target responsible for any disease is recognized.
What are the difficulties of AI in drug development?
There is a lack of transparency, lack of data availability and also biases in data.